Improved sepsis surveillance using a fully automated electronic health record-based algorithm compared to diagnostic coding.

Background

Accurate diagnostic coding of sepsis is essential for surveillance, resource allocation, and health policy planning. Studies assessing the usability of claims-based data (ICD-10 codes) compared to clinical criteria for sepsis surveillance are needed.

Objectives

To assess the concordance between ICD-10 diagnostic coding of sepsis and classification using a previously validated fully automated electronic health record (EHR)-based algorithm applying Sepsis-3 criteria.

Methods

We conducted an observational study, including adult in-hospital admissions during 2016-2024 at Karolinska University Hospital and 2022-2024 at three hospitals in Region Västerbotten, Sweden. The Sepsis-3 algorithm identified suspected infection combined with an increase in Sequential Organ Failure Assessment (SOFA) score ≥2 points. Sepsis ICD-10 codes were categorised as explicit or specific (R65.1, R57.2). Concordance was evaluated using descriptive and kappa statistics, and time trends were analysed.

Results

Among 174,343 admissions during the common study period (2022-2024), the Sepsis-3 algorithm classified sepsis in 11.4% of admissions at Karolinska and 6.2% in Västerbotten, compared to 2.5% and 1.2% with explicit codes and 1.4% and 0.6% with specific codes, respectively. Concordance of diagnostic codes with the Sepsis-3 algorithm was low (kappa 0.21 and 0.14 for explicit and specific codes at Karolinska; 0.15 and 0.09 in Västerbotten). During the study period 2016-24 at Karolinska, introduction of an automated SOFA calculator in the EHR system was associated with increased usage of specific sepsis codes but remained far below algorithm-based classification.

Conclusion

Automated EHR-based algorithms allow for data-driven sepsis surveillance and may support more reliable diagnostic coding practices.